Author(s)

Chunlei Yang, Jinye Peng, Jianping Fan

1CSIRO Sustainable Ecosystems, Carmody Road, St. Lucia Queensland, Australia 2CSIRO Sustainable Ecosystems, Highett, Australia.
CSIRO Sustainable Ecosystems, Highett, Australia.

Near-duplicate image detection is a necessary operation to refine image search results for efficient user exploration. The existences of large amounts of near duplicates require fast and accurate automatic near-duplicate detection methods. We have designed a coarse-to-fine near duplicate detection framework to speed-up the process and a multi-modal integra-tion scheme for accurate detection. The duplicate pairs are detected with both global feature (partition based color his-togram) and local feature (CPAM and SIFT Bag-of-Word model). The experiment results on large scale data set proved the effectiveness of the proposed design.

Near-Duplicate Detection; Coarse-To-Fine Framework; Multi-Modal Feature Integration

C. Yang, J. Peng and J. Fan, "Speed-up Multi-modal Near Duplicate Image Detection," Open Journal of Applied Sciences, Vol. 3 No. 1B, 2013, pp. 16-21. doi: 10.4236/ojapps.2013.31B004.